AF1 Urban Environmental Planning WP 5 Urban Transport



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Adaptation to Global to Climate Climate Change Change AF1 Urban Environmental Planning WP 5 Urban Transport Prof. Dr. Günter Emberger Dr. Paul Pfaffenbichler Vienna University of Technology Institute of Transportation Research Center of Transport Planning and Traffic Engineering

Objectives of WP5 Urban Transport The objective of work package 5 Urban Transport is to assess the potential of land use and transport strategies to improve the effectiveness of the urban transport system and to reduce its greenhouse gas emissions.

Adaptation to Global to Climate Climate Change Change Urban Flooding Urban Climate Urban Energy Urban Transport Public transport in HCMC is very poorly developed. Urban Transport in HCMC HCMC Number Mode share Motorbikes ~3 million 60%-70% Public Transport 10% Motorised vehicle ownership (per 1,000 residents) City Motorcycles Cars Total Vienna 42 417 459 Hanoi 412 43 455 Most traffic related impacts on the environment derive from private passenger traffic. (Sources: Magistratsabteilung 66 - Statistisches Amt 2002; TDSI 2004)

Adaptation to Global to Climate Climate Change Change Urban Flooding Urban Climate Urban Energy Urban Transport Asso. Prof. Nguyen Ba Hoang, PhD. Dean Civil Engineer faculty HoChiMinh University of Transport. VN Research & Cooperation Partners Nguyen Thi Phuong Hien Director Transport Environment and Development Center (TEDEC) Transport Development and Strategy Institute (TDSI) Ministry of Transport of Vietnam 162 Tran Quang Khai, Hanoi

The strategic dynamic land use and transport interaction model MARS (Metropolitan Activity Relocation Simulator) Models so far: Vienna (AUT) Madrid (ESP) Leeds (UK) Edinburgh (UK) Oslo (NOR) Helsinki (S) Chiang Mai (THA) Ubon Ratchantani (THA) Hanoi (VN) www.ivv.tuwien.ac.at/forschung/mars-metropolitan-activity-relocation-simulator.html

The MARS flight simulator TRANSPORT POLICIY INSTRUMENTS SLOW Motorcycle Car Public transport Car Examples for potential scenarios Improving bus system Increasing road capacity Metro System population growth

The MARS model output Results over Time 0.8 0.6 0.4 Mode Share Peak - motorized 0.2 0 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 Time (Year) ms car peak : Actual Run ms moto peak : Actual Run ms car peak : Do-Nothing ms moto peak : Do-Nothing Percent Percent Percent Percent

The MARS flight simulator model of Hanoi Results in time and space

Tasks I Set up MARS Environment for HCMC Adaption of zoning system (24 districtcs, based of AF1 information) preparation of input data files set up of graphical dynamic GIS userinterface (AniMAP) Integration of motorbikes in MARS as an additional means of transport (slow, car,pt,motorcycle, rail) Literature review HCMC transport masterplan, Verkehrserhebung HCMC 1997, HEPA Traffic counts data, MVA CUBE model, Statistical yearbook HCMC, Vietnam Infrastructure Strategy other AF1 & AF2 data sources, etc...

Tasks II Data Collection excercise in collaboration with Vietnamese Partners regarding population, employment, income, hh-size travel times, travel costs per means of transport estimations of housing costs land use, developable land modal split, traffic counts etc...

Concrete activities with our Partners I Empirical investigations regarding road capacities Speed measurements on 10 different roads separated for lorries, buses, car, cycle and pedestrians for peak and offpeak. Analysis of the average occupancy rate of the vehicles Analysis of the throughput of roads Measurement of transport related noise emissions Estimation of travel speeds by travelling from city center to specific locations during peak/ off peak hours using different means of transport (bike, motorbike, public transport, car, etc..)

Concrete activities with our Partners II Providing information in English of existing / planned further steps regarding land use and transport plans for HCMC (Compilation of relevant documents and summaries in English) partly finished Summary of traffic related laws Information on enforcement Support on scenario definitions (such as assessment of the Metro system, impact analysis of road network extensions, car ownership development, etc ) At the moment we are in right the middle of this data gathering process!!

Further outlook Thursday 2 nd April 09: HCMC UoT - International Symposium of transport planning and influence of climate change Set up MARS Model /calibration /scenarios Future: Organising Training Courses in HCMC

Adaptation to Global to Climate Climate Change Change Thank you for your attention! Prof. Dr. Günter Emberger VN Mobile: 01265427640 guenter.emberger@tuwien.ac.at Dr. Paul Pfaffenbichler Mobile VN: 01265427640 paul.pfaffenbichler@ivv.tuwien.ac.at Vienna University of Technology Institute of Transportation Research Center of Transport Planning and Traffic Engineering

The MARS Hanoi model

The MARS flight simulator model of Hanoi The land use part Land available for H4- Land - Price development + - H2+ + - H3- Attractiveness to + develop + New Rent Housing H1- + + Housing Excess demand stock - for housing + + + Accessibility Population Green areas

Model Set Up Data Requirements population, employment, income, hh-size travel times, travel costs per means of transport estimations of housing costs land use, developable land modal split, traffic counts etc...

A simple SD model of the interaction between car ownership and land and energy consumption 600 (veh/1000 inh) 400 (year 0 = 100) 20 (km/h) 300 (veh/1000 inh) 200 (year 0 = 100) 10 (km/h) 0 (veh/1000 inh) 0 (year 0 = 100) 0 (km/h) M S M S M C P C P C P M S C P P M M P M P M M M P P S S S S S S C C C C C 0 4 8 12 16 20 24 28 Vehicle stock[moto] : Current M M M M M M (veh/1000 inh) Vehicle stock[car] : Current C C C C C C C (veh/1000 inh) Petrol consumption P P P P P P P P (year 0 = 100) Speed S S S S S S S S S S (km/h) Source: Pfaffenbichler et. al. (2007)

What we plan to do in the project Set up a MARS Model for HCMC Set up an fleet composition model Expected results forcast of modal shares, accidents, emissions (CO 2 ), congestion, land use development, and many other indicators What we need Information based on zones regarding population, motorisation rate, public transport, modal shares, household income, land use, etc.

TU Vienna Institut for Transport Planning and Traffic Enginering TU Vienna founded 1815 21 Bachelorstudies and 41 Masterstudies, 5 Lectorship-studies, 8 faculties, 230 partner universities 17.579 students; 151 Professors, 2400 Research Staff, 3500 total staff; approx. 155 Mio. EUR budget plus approx. 45 Mio. EUR projects Institute for Transport Planning and Traffic Engineering founded 1960ies, 14 staff, 4 professors, involvement in >30 international projects Main activities: teaching, research, planning, training

Background of TUW-IVV www.ivv.tuwien.ac.at/forschung/projekte/international-projects/sparkle-2004.html Involved Countries: UK, A, Thailand, Laos, Vietnam, Cambodia Objectives (2004-2006) to promote and transfer knowledge to the countries of South East Asia on the process of developing sustainable urban land use and transport policies to provide technical training to local planners and decision-makers on how to use scientific and logical approaches to formulate a sustainable land use and transport policy.

MARS applcations Europe Europe

Asia MARS applcations Asia

A simple SD model of the interaction between car ownership and land and energy consumption Vehicle stock T=0 Volume/Capacity T=0 Volume/Capacity <Built capacity> V free V congested Alpha Beta Vehicle inflow Vehicle stock Vehicle outflow Space consumption car/moto Distance V congested T-1 Purchase price <Time> Potential vehicles T Parameter Lifespan Energy mode <Vehicle stock T=0> Energy T=0 New capacity decision Built capacity Capacity in Threshold construction Construction time <V congested> Source: Pfaffenbichler et. al. (2007) Energy relative <Vehicle stock>

A SD model of the interaction between car ownership and land and energy consumption A System Dynamics model was created to simulate the interaction between car and motorcycle ownership, infrastructure development and land and energy consumption. This model was used to give a first estimation of the effects of the WTO accession of Vietnam.